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A survey on vision-based driver distraction analysis
16 references·1 citing·38 second hop
A survey on vision-based driver distraction analysis (2021)A survey on vision-based driver distracti…Driver Distraction Identification with an Ensemble of Convolutional Neural Networks (2019)Driver Distraction Identifica…Driver Activity Recognition for Intelligent Vehicles: A Deep Learning Approach (2019)Driver Activity Recognition f…A Comprehensive Survey of Driving Monitoring and Assistance Systems (2019)A Comprehensive Survey of Dri…Take-Over Time in Highly Automated Vehicles (2018)Take-Over Time in Highly Auto…Detection of Distracted Driver Using Convolutional Neural Network (2018)Detection of Distracted Drive…Takeover Time in Highly Automated Vehicles: Noncritical Transitions to and From Manual Control (2017)Takeover Time in Highly Autom…Real-time Distracted Driver Posture Classification (2017)Real-time Distracted Driver P…Understanding the impacts of mobile phone distraction on driving performance: A systematic review (2016)Understanding the impacts of …Looking at Humans in the Age of Self-Driving and Highly Automated Vehicles (2016)Looking at Humans in the Age …Driver Behavior Analysis for Safe Driving: A Survey (2015)Driver Behavior Analysis for …Visual Analysis of Eye State and Head Pose for Driver Alertness Monitoring (2013)Visual Analysis of Eye State …Driver Inattention Monitoring System for Intelligent Vehicles: A Review (2011)Driver Inattention Monitoring…Driver distraction and driver inattention: Definition, relationship and taxonomy (2011)Driver distraction and driver…Defining Driver Distraction (2008)Defining Driver DistractionReal-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance (2002)Real-Time Eye, Gaze, and Face…NHTSA DRIVER DISTRACTION RESEARCH: PAST, PRESENT, AND FUTURE (2001)NHTSA DRIVER DISTRACTION RESE…AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perception (2023)AIDE: A Vision-Driven Multi-V…Cognitive Reliability and Error Analysis Method (CREAM) (1998)Stream of consciousness (1998)Real-Time Detection System of Driver Distraction Using Machine Learning (2013)Recent Trends in Driver Safety Monitoring Systems: State of the Art and Challenges (2016)Driver Distraction Detection Methods: A Literature Review and Framework (2021)Measurement of Situation Awareness in Dynamic Systems (1995)Toward a Theory of Situation Awareness in Dynamic Systems (1995)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Driver Fatigue Detection Systems: A Review (2018)Driver behavior detection and classification using deep convolutional neural networks (2020)Real-Time Detection of Driver Cognitive Distraction Using Support Vector Machines (2007)Driver Drowsiness Classification Using Fuzzy Wavelet-Packet-Based Feature-Extraction Algorithm (2010)Driver Distraction Detection Using Semi-Supervised Machine Learning (2015)MIT Advanced Vehicle Technology Study: Large-Scale Naturalistic Driving Study of Driver Behavior and Interaction With Automation (2019)Effects of visual and cognitive load in real and simulated motorway driving (2005)Detecting Driver Drowsiness Based on Sensors: A Review (2012)Heart Rate Variability-Based Driver Drowsiness Detection and Its Validation With EEG (2018)Real-Time Driver-Drowsiness Detection System Using Facial Features (2019)Examining the Impact of Cell Phone Conversations on Driving Using Meta-Analytic Techniques (2006)A meta-analysis of the effects of cell phones on driver performance (2008)Engineering a safer world: systems thinking applied to safety (2012)Effects of road infrastructure and traffic complexity in speed adaptation behaviour of distracted drivers (2017)On identification of driving-induced stress using electroencephalogram signals: A framework based on wearable safety-critical scheme and machine learning (2019)Ironies of automation (1983)A Critical View of Driver Behavior Models: What Do We Know, What Should We Do? (1985)Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research (1988)Determinants of take-over time from automated driving: A meta-analysis of 129 studies (2019)Toward Computational Simulations of Behavior During Automated Driving Takeovers: A Review of the Empirical and Modeling Literatures (2019)Driver drowsiness detection with eyelid related parameters by Support Vector Machine (2008)On the Roles of Eye Gaze and Head Dynamics in Predicting Driver's Intent to Change Lanes (2009)Towards Detection of Bus Driver Fatigue Based on Robust Visual Analysis of Eye State (2016)Intelligent In‐Vehicle Interaction Technologies (2021)Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles (2022)HCF: A Hybrid CNN Framework for Behavior Detection of Distracted Drivers (2020)Toward human-vehicle collaboration: Review and perspectives on human-centered collaborative automated driving (2021)Safety implications of providing real-time feedback to distracted drivers (2006)DriveSafe: An app for alerting inattentive drivers and scoring driving behaviors (2014)Assessing Cognitive Distraction in the Automobile (2015)
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References

  • 2011Driver Inattention Monitoring System for Intelligent Vehicles: A Review728 cited
  • 2017Takeover Time in Highly Automated Vehicles: Noncritical Transitions to and From Manual Control691 cited
  • 2002Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance561 cited
  • 2011Driver distraction and driver inattention: Definition, relationship and taxonomy503 cited
  • 2015Driver Behavior Analysis for Safe Driving: A Survey404 cited
  • 2019Driver Activity Recognition for Intelligent Vehicles: A Deep Learning Approach402 cited
  • 2016Understanding the impacts of mobile phone distraction on driving performance: A systematic review319 cited
  • 2019Driver Distraction Identification with an Ensemble of Convolutional Neural Networks307 cited
  • 2001NHTSA DRIVER DISTRACTION RESEARCH: PAST, PRESENT, AND FUTURE281 cited
  • 2013Visual Analysis of Eye State and Head Pose for Driver Alertness Monitoring253 cited
  • 2008Defining Driver Distraction222 cited
  • 2019A Comprehensive Survey of Driving Monitoring and Assistance Systems221 cited
  • 2016Looking at Humans in the Age of Self-Driving and Highly Automated Vehicles218 cited
  • 2017Real-time Distracted Driver Posture Classification193 cited
  • 2018

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Take-Over Time in Highly Automated Vehicles
189 cited
  • 2018Detection of Distracted Driver Using Convolutional Neural Network184 cited
  • Cited by

    • 2023AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perception68 cited